Inferring entire spiking activity from local field potentials

Nur Ahmadi,Timothy G Constandinou,Christos-Savvas Bouganis

doi:10.1038/s41598-021-98021-9

Nur Ahmadi, Timothy G Constandinou + Show 1 more

Open Access

https://doi.org/10.1038/s41598-021-98021-9

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Abstract

Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes. Previous studies have shown that spikes, in the form of single-unit activity (SUA) or multiunit activity (MUA), can be inferred solely from LFPs with moderately good accuracy. SUA and MUA are typically extracted via threshold-based technique which may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). Another type of spiking activity, referred to as entire spiking activity (ESA), can be extracted by a threshold-less, fast, and automated technique and has led to better performance in several tasks. However, its relationship with the LFPs has not been investigated. In this study, we aim to address this issue by inferring ESA from LFPs intracortically recorded from the motor cortex area of three monkeys performing different tasks. Results from long-term recording sessions and across subjects revealed that ESA can be inferred from LFPs with good accuracy. On average, the inference performance of ESA was consistently and significantly higher than those of SUA and MUA. In addition, local motor potential (LMP) was found to be the most predictive feature. The overall results indicate that LFPs contain substantial information about spiking activity, particularly ESA. This could be useful for understanding LFP-spike relationship and for the development of LFP-based BMIs.

Highlights

Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes
We evaluated and compared the informativeness of six different LFP features: the smoothed time-domain amplitude of LFP known as local motor potential (LMP) and average power spectra within five frequency bands
The present study investigates the relationship between local field potential (LFP) and entire spiking activity (ESA) by asking whether we can infer ESA solely from LFPs

Summary

Introduction

Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes. SUA and MUA are typically extracted via threshold-based technique which may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). MUA—sometimes called multiunit spike (MSP)—refers to all the detected spikes (without spike sorting) and represents the aggregate spikes from an ensemble of neurons within a radius of ∼ 140–300 μm in the vicinity of the electrode t ip[9,10,11,12] Extracting both SUA and MUA relies on setting the threshold value (manually or automatically) which could be problematic when the recordings exhibit a low SNR or high variation over time. ESA has been shown to yield more accurate and robust decoding of hand kinematics compared to SUA and MUA from three monkeys performing different tasks[23]

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